Perceptrons: expanded edition
Multilayer feedforward networks are universal approximators
Neural Networks
Phonetically-based multi-layered neural networks for classification
Speech Communication - Neurospeech
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
An introduction to neural and electronic networks
An introduction to neural and electronic networks
Introduction to matrix analysis (2nd ed.)
Introduction to matrix analysis (2nd ed.)
Fuzzy pattern classification and the connectionist approach
Pattern Recognition Letters - Special issue on fuzzy set technology in pattern recognition
Are Multilayer Perceptrons Adequate for Pattern Recognition and Verification?
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Convergent Generalized Back-Propagation Algorithm with Constant Learning Rate
Neural Processing Letters
A Fast Neural Learning Vision System for Crowd Estimation at Underground Stations Platform
Neural Processing Letters
ACM Transactions on Graphics (TOG)
Computerised Auto-Scoring System Based Upon Feature Extraction and Neural Network Technologies
Journal of Intelligent and Robotic Systems
A Fast Heuristic Global Learning Algorithm for Multilayer Neural Networks
Neural Processing Letters
Unified Integration of Explicit Knowledge and Learning by Example in Recurrent Networks
IEEE Transactions on Knowledge and Data Engineering
A global optimum approach for one-layer neural networks
Neural Computation
Neural Network Learning Using Low-Discrepancy Sequence
AI '99 Proceedings of the 12th Australian Joint Conference on Artificial Intelligence: Advanced Topics in Artificial Intelligence
A Note on Learning Automata Based Schemes for Adaptation of BP Parameters
IDEAL '00 Proceedings of the Second International Conference on Intelligent Data Engineering and Automated Learning, Data Mining, Financial Engineering, and Intelligent Agents
Proceedings of the Second European Workshop on Genetic Programming
Efficient Learning in Adaptive Processing of Data Structures
Neural Processing Letters
Discovering efficient learning rules for feedforward neural networks using genetic programming
Recent advances in intelligent paradigms and applications
Genetic Evolution Processing of Classification
IEEE Transactions on Knowledge and Data Engineering
An effective learning of neural network by using RFBP learning algorithm
Information Sciences—Informatics and Computer Science: An International Journal
2005 Special Issue: The loading problem for recursive neural networks
Neural Networks - Special issue on neural networks and kernel methods for structured domains
Improved sign-based learning algorithm derived by the composite nonlinear Jacobi process
Journal of Computational and Applied Mathematics - Special issue: The international conference on computational methods in sciences and engineering 2004
Parameterisation and evaluation of a Bayesian network for use in an ecological risk assessment
Environmental Modelling & Software
Probabilistic based recursive model for adaptive processing of data structures
Expert Systems with Applications: An International Journal
A novel ANN-based service selection model for ubiquitous computing environments
Journal of Network and Computer Applications
A Study on Chronic Obstructive Pulmonary Disease Diagnosis Using Multilayer Neural Networks
Journal of Medical Systems
A comparative study on thyroid disease diagnosis using neural networks
Expert Systems with Applications: An International Journal
Particle swarm optimization with adaptive population size and its application
Applied Soft Computing
Expert Systems with Applications: An International Journal
A comparative study on diabetes disease diagnosis using neural networks
Expert Systems with Applications: An International Journal
Information Processing and Management: an International Journal
On the efficient classification of data structures by neural networks
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Computational capabilities of graph neural networks
IEEE Transactions on Neural Networks
The multi-phase method in fast learning algorithms
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartI
Avoiding local minima in feedforward neural networks by simultaneous learning
AI'07 Proceedings of the 20th Australian joint conference on Advances in artificial intelligence
ICNC'09 Proceedings of the 5th international conference on Natural computation
Chest diseases diagnosis using artificial neural networks
Expert Systems with Applications: An International Journal
A reliable resilient backpropagation method with gradient ascent
ICIC'06 Proceedings of the 2006 international conference on Intelligent computing: Part II
Indoor location sensing using geo-magnetism
MobiSys '11 Proceedings of the 9th international conference on Mobile systems, applications, and services
Theory and practice on information granule matrix
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
An approach based on probabilistic neural network for diagnosis of Mesothelioma's disease
Computers and Electrical Engineering
Image compression with a dynamic autoassociative neural network
Mathematical and Computer Modelling: An International Journal
Global hybrid ant bee colony algorithm for training artificial neural networks
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part I
Addressing the local minima problem by output monitoring and modification algorithms
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
Magnified gradient function to improve first-order gradient-based learning algorithms
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
G-HABC Algorithm for Training Artificial Neural Networks
International Journal of Applied Metaheuristic Computing
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
An Optimization Rule for In Silico Identification of Targeted Overproduction in Metabolic Pathways
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Global Artificial Bee Colony-Levenberq-Marquardt GABC-LM Algorithm for Classification
International Journal of Applied Evolutionary Computation
Let a biogeography-based optimizer train your Multi-Layer Perceptron
Information Sciences: an International Journal
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The authors propose a theoretical framework for backpropagation (BP) in order to identify some of its limitations as a general learning procedure and the reasons for its success in several experiments on pattern recognition. The first important conclusion is that examples can be found in which BP gets stuck in local minima. A simple example in which BP can get stuck during gradient descent without having learned the entire training set is presented. This example guarantees the existence of a solution with null cost. Some conditions on the network architecture and the learning environment that ensure the convergence of the BP algorithm are proposed. It is proven in particular that the convergence holds if the classes are linearly separable. In this case, the experience gained in several experiments shows that multilayered neural networks (MLNs) exceed perceptrons in generalization to new examples.